Currently, cellular networks are one of the essential communication methods for people. Providing proper coverage for the users and also offering high-quality services to them are two of the most important issues of concern in cellular networks. The fifth-generation cellular communication networks can provide higher data transmission rates, which lead to a higher quality of service but this hig...

to use soil hydrology processes (shp) models, which have increasingly extended during the last years, comprehensive knowledge about these models and their modeling approaches seems to be necessary. the modeling approaches can be categorized as either classical or non-classical. classical approaches mainly model the shp through solving the general unsaturated flow (richards) equation, numericall...

The Hybrid neural Fuzzy Inference System (HyFIS) is a multilayer adaptive neural fuzzy system for building and optimizing fuzzy models using neural networks. In this paper, the fuzzy Yager inference scheme, which is able to emulate the human deductive reasoning logic, is integrated into the HyFIS model to provide it with a firm and intuitive logical reasoning and decision-making framework. In a...

Critical care providers are faced with resource shortages and must find ways to effectively plan their resource utilization. Neural networks provide a new method for evaluating trauma patient (and other medical patient) level of illness and accurately predicting a patient’s length of stay at the critical care facility. Backpropagation, radial-basis-function, and fuzzy ARTMAP neural networks are...

Aircraft burst fault is uncertainty and ambiguity. Considering QAR data as the research object, the fault diagnosis system based on the T-S fuzzy neural network combined with aircraft maintenance processes is built. First, the system designs the network performance oversight function to improve genetic neural network program. Then the fuzzy logic is used to deal with fuzzy rules, which can dete...

In this paper, we present a method of face recognition based on fuzzy clustering and parallel neural networks. Two sets of images are acquired: the frontal images and the slight angle profile face images. In the case of the slight angle profile face images,a head model is built in order to compensate the pose. In the second step, we propose a method for face recognition based on fuzzy clusterin...

In this paper, some application of computational intelligence techniques in active networking technology well be presented. Computational intelligent techniques, e.g., neural networks, fuzzy systems, neuro-fuzzy systems, and evolutionary algorithms have been successfully applied for many engineering problems. The introduction of active networking adds a high degree of flexibility in customizing...

This paper explores different techniques for extracting propositional rules from linguistic rule neural networks and fuzzy rules from fuzzy neural networks. The applicability and suitability of different types of rules to different problems is analyzed. Hierarchical rule structures are considered where the higher the level is the smaller the number of rules which become more vague and more appr...

In this paper we propose a novel training algorithm for RBF networks that is based on extended kalman filter and fuzzy logic.After the user choose how many prototypes to include in the network, the extended kalman filter simultancously solves for the prototype vectors and the weight matrix.The fuzzy logic is used to cope with the devergence problem caused by the insufficiently known a priori fi...

In this paper, we propose new sets of criteria for exponential robust stability of Takagi-Sugeno (T-S) fuzzy Hopfield neural networks. The L2−L∞ approach is applied to obtain new sets of stability criteria, under which T-S fuzzy Hopfield neural networks reduce the effect of external input to a prescribed level. These sets of criteria are presented based on the matrix norm and linear matrix ineq...